SoroushVahidi/scidocs huggingface dataset:
Moral dilemmas in cognitive neuroscience of moral decision-making: A principled review
(2012)

Moral dilemma tasks have been a much appreciated experimental paradigm in empirical studies on moral cognition for decades and have, more recently, also become a preferred paradigm in the field of cognitive neuroscience of moral decision-making. Yet, studies using moral dilemmas suffer from two main shortcomings: they lack methodological homogeneity which impedes reliable comparisons of results across studies, thus making a metaanalysis manifestly impossible; and second, they overlook control of relevant design parameters. In this paper, we review from a principled standpoint the studies that use moral dilemmas to approach the psychology of moral judgment and its neural underpinnings. We present a systematic review of 19 experimental design parameters that can be identified in moral dilemmas. Accordingly, our analysis establishes a methodological basis for the required homogeneity between studies and suggests the consideration of experimental aspects that have not yet received much attention despite their relevance.
Interlingua based Sanskrit-English machine translation
(2017)

This paper is based on the work towards developing a machine translation system for Sanskrit to English. An interlingua based machine translation system in Paninian framework was developed in this work. As lexical functional grammar can handle semantic information along with syntactic analysis, the proposed system uses lexical functional grammar in different levels of analysis phase. In this system the given Sanskrit text is first converted to an intermediate notation called interlingua. This notation is then used for mapping to the target language, English, and generates the translated output. The proposed system works in the translation of simple and complex sentences in the given corpus. The karaka analysis system of Panini is used for the semantic analysis.
Development and field test of novel two-wheeled UAV for bridge inspections
(2017)

This paper presents the development and field test of a novel unmanned aerial vehicle (UAV) for bridge inspections. The proposed UAV, which consists of a quadrotor, a cylindrical cage installed in it, and two spokeless wheels freely rotating around the cage, can climb and run on the bridge surface. Its structure improves durability and reduces air resistance compared with conventional UAVs with a cage or wheels. These advantages expand the uses of the UAV in various fields. This paper evaluates the effectiveness of the proposed UAV in real-world bridge inspection scenarios. We tested basic locomotion and measured air resistances. Experimental results on bridges demonstrated the ability to inspect various locations on bridges that are difficult for human inspectors to access.
An 87 fJ/conversion-step 12 b 10 MS/s SAR ADC using a minimum number of unit capacitors
(2014)

This work proposes a 12 b 10 MS/s 0.11 lm CMOS successive-approximation register ADC based on a C-R hybrid DAC for low-power sensor applications. The proposed C-R DAC employs a 2-step split-capacitor array of upper seven bits and lower five bits to optimize power consumption and chip area at the target speed and resolution. A VCM-based switching method for the most significant bit and reference voltage segments from an insensitive R-string for the last two least significant bits minimize the number of unit capacitors required in the C-R hybrid DAC. The comparator accuracy is improved by an open-loop offset cancellation technique in the first-stage pre-amp. The prototype ADC in a 0.11 lm CMOS process demonstrates the measured differential nonlinearity and integral nonlinearity within 1.18 LSB and 1.42 LSB, respectively. The ADC shows a maximum signal-to-noise-and-distortion ratio of 63.9 dB and a maximum spurious-free dynamic range of 77.6 dB at 10 MS/s. The ADC with an active die area of 0.34 mm consumes 1.1 mW at 1.0 V and 10 MS/s, corresponding to a figure-of-merit of 87 fJ/conversion-step.
Assessment of degree of risk from sources of microbial contamination in cleanrooms ; 3 : Overall application
(2017)

The European Commission and the Food and Drug Administration in the USA suggest that risk management and assessment methods should be used to identify and control sources of microbial contamination1,2. A risk management method has been described by Whyte3,4 that is based on the Hazard Analysis and Critical Control Point (HACCP) system but reinterpreted for use in cleanrooms, and called Risk Management of Contamination (RMC). This method is also described in the PHSS Technical Monograph No 145 and has the following steps.
Mindfulness and Meditation Practice as Moderators of the Relationship between Age and Subjective Wellbeing among Working Adults
(2017)

Promoting the health and wellbeing of an aging and age-diverse workforce is a timely and growing concern to organizations and to society. To help address this issue, we investigated the relationship between age and subjective wellbeing by examining the moderating role of mindfulness in two independent studies. In study 1, trait mindfulness was examined as a moderator of the relationship between age and vitality and between age and work-family balance in a sample of 240 participants. In study 2, data from the second phase of the Midlife Development in the USA (MIDUS II) project was used to investigate mindful-practice (i.e., meditation) as a moderator of the relationships between age and multiple measures of subjective wellbeing (life satisfaction, psychological health, physical health) in a sample of 2477 adults. Results revealed that mindfulness moderates the relationship between age and multiple indicators of subjective wellbeing. In addition, study 2 results indicated that individuals who reported that they mediated often combined with those who reported they meditated a lot reported better physical health than those who reported that they never meditate. The findings suggest that cultivating mindfulness can be a proactive tool for fostering health and subjective wellbeing in an aging and agediverse workforce.
A Survey of Intrusion Detection Techniques
(2013)

Intrusion detection is an alternative to the situation of the security violation.Security mechanism of the network is necessary against the threat to the system. There are two types of intruders: external intruders, who are unauthorized users of the machines they attack, and internal intruders, who have permission to access the system with some restrictions. This paper describes a brief overview of various intrusion detection techniques such as fuzzy logic, neural network, pattern recognition methods, genetic algorithms and related techniques is presented. Among the several soft computing paradigms, fuzzy rule-based classifiers, decision trees, support vector machines, linear genetic programming is model fast and efficient intrusion detection systems. KeywordsIntroduction, intrusion detection methods, misuse detection techniques, anomaly detection techniques, genetic algorithms.
Face Recognition with Local Binary Patterns, Spatial Pyramid Histograms and Naive Bayes Nearest Neighbor Classification
(2009)

Face recognition algorithms commonly assume that face images are well aligned and have a similar pose -- yet in many practical applications it is impossible to meet these conditions. Therefore extending face recognition to unconstrained face images has become an active area of research. To this end, histograms of Local Binary Patterns (LBP) have proven to be highly discriminative descriptors for face recognition. Nonetheless, most LBP-based algorithms use a rigid descriptor matching strategy that is not robust against pose variation and misalignment. We propose two algorithms for face recognition that are designed to deal with pose variations and misalignment. We also incorporate an illumination normalization step that increases robustness against lighting variations. The proposed algorithms use descriptors based on histograms of LBP and perform descriptor matching with spatial pyramid matching (SPM) and Naive Bayes Nearest Neighbor (NBNN), respectively. Our contribution is the inclusion of flexible spatial matching schemes that use an image-to-class relation to provide an improved robustness with respect to intra-class variations. We compare the accuracy of the proposed algorithms against Ahonen's original LBP-based face recognition system and two baseline holistic classifiers on four standard datasets. Our results indicate that the algorithm based on NBNN outperforms the other solutions, and does so more markedly in presence of pose variations.
Energy-Efficient Resource Allocation for Mobile-Edge Computation Offloading
(2017)

Mobile-edge computation offloading (MECO) off-loads intensive mobile computation to clouds located at the edges of cellular networks. Thereby, MECO is envisioned as a promising technique for prolonging the battery lives and enhancing the computation capacities of mobiles. In this paper, we study resource allocation for a multiuser MECO system based on time-division multiple access (TDMA) and orthogonal frequency-division multiple access (OFDMA). First, for the TDMA MECO system with infinite or finite cloud computation capacity, the optimal resource allocation is formulated as a convex optimization problem for minimizing the weighted sum mobile energy consumption under the constraint on computation latency. The optimal policy is proved to have a threshold-based structure with respect to a derived offloading priority function, which yields priorities for users according to their channel gains and local computing energy consumption. As a result, users with priorities above and below a given threshold perform complete and minimum offloading, respectively. Moreover, for the cloud with finite capacity, a sub-optimal resource-allocation algorithm is proposed to reduce the computation complexity for computing the threshold. Next, we consider the OFDMA MECO system, for which the optimal resource allocation is formulated as a mixed-integer problem. To solve this challenging problem and characterize its policy structure, a low-complexity sub-optimal algorithm is proposed by transforming the OFDMA problem to its TDMA counterpart. The corresponding resource allocation is derived by defining an average offloading priority function and shown to have close-to-optimal performance in simulation.
Offloading in Mobile Cloudlet Systems with Intermittent Connectivity
(2015)

The emergence of mobile cloud computing enables mobile users to offload applications to nearby mobile resource-rich devices (i.e., cloudlets) to reduce energy consumption and improve performance. However, due to mobility and cloudlet capacity, the connections between a mobile user and mobile cloudlets can be intermittent. As a result, offloading actions taken by the mobile user may fail (e.g., the user moves out of communication range of cloudlets). In this paper, we develop an optimal offloading algorithm for the mobile user in such an intermittently connected cloudlet system, considering the users' local load and availability of cloudlets. We examine users' mobility patterns and cloudlets' admission control, and derive the probability of successful offloading actions analytically. We formulate and solve a Markov decision process (MDP) model to obtain an optimal policy for the mobile user with the objective to minimize the computation and offloading costs. Furthermore, we prove that the optimal policy of the MDP has a threshold structure. Subsequently, we introduce a fast algorithm for energy-constrained users to make offloading decisions. The numerical results show that the analytical form of the successful offloading probability is a good estimation in various mobility cases. Furthermore, the proposed MDP offloading algorithm for mobile users outperforms conventional baseline schemes.
Above the Clouds: A Berkeley View of Cloud Computing
(2009)

Cloud Computing, the long-held dream of computing as a utility, has the potential to transform a large part of the IT industry, making software even more attractive as a service and shaping the way IT hardware is designed and purchased. Developers with innovative ideas for new Internet services no longer require the large capital outlays in hardware to deploy their service or the human expense to operate it. They need not be concerned about overprovisioning for a service whose popularity does not meet their predictions, thus wasting costly resources, or underprovisioning for one that becomes wildly popular, thus missing potential customers and revenue. Moreover, companies with large batch-oriented tasks can get results as quickly as their programs can scale, since using 1000 servers for one hour costs no more than using one server for 1000 hours. This elasticity of resources, without paying a premium for large scale, is unprecedented in the history of IT. Cloud Computing refers to both the applications delivered as services over the Internet and the hardware and systems software in the datacenters that provide those services. The services themselves have long been referred to as Software as a Service (SaaS). The datacenter hardware and software is what we will call a Cloud. When a Cloud is made available in a pay-as-you-go manner to the general public, we call it a Public Cloud; the service being sold is Utility Computing. We use the term Private Cloud to refer to internal datacenters of a business or other organization, not made available to the general public. Thus, Cloud Computing is the sum of SaaS and Utility Computing, but does not include Private Clouds. People can be users or providers of SaaS, or users or providers of Utility Computing. We focus on SaaS Providers (Cloud Users) and Cloud Providers, which have received less attention than SaaS Users. From a hardware point of view, three aspects are new in Cloud Computing.
2.4 to 61 GHz Multiband Double-Directional Propagation Measurements in Indoor Office Environments
(2018)

This paper presents the details and results of double-directional propagation measurements carried out in two indoor office environments: a semi-open, cubicle-type office space and a more traditional work environment with closed offices. The measurements cover seven frequency bands from 2.4 to 61 GHz, permitting the propagation characteristics to be compared over a wide range of candidate radio frequencies for next-generation mobile wireless systems, including ultra high frequency and millimeter-wave bands. A novel processing algorithm is introduced for the expansion of multiband measurement data into sets of discrete multipath components. Based on the resulting multipath parameter estimates, models are presented for frequency-dependent path loss, shadow fading, copolarization ratio, delay spread, and angular spreads, along with their interfrequency correlations. Our results indicate a remarkably strong consistency in multipath structure over the entire frequency range considered.
Wavelet based real-time smoke detection in video
(2005)

A method for smoke detection in video is proposed. It is assumed the camera monitoring the scene is stationary. Since the smoke is semi-transparent, edges of image frames start loosing their sharpness and this leads to a decrease in the high frequency content of the image. To determine the smoke in the field of view of the camera, the background of the scene is estimated and decrease of high frequency energy of the scene is monitored using the spatial wavelet transforms of the current and the background images. Edges of the scene are especially important because they produce local extrema in the wavelet domain. A decrease in values of local extrema is also an indicator of smoke. In addition, scene becomes grayish when there is smoke and this leads to a decrease in chrominance values of pixels. Periodic behavior in smoke boundaries and convexity of smoke regions are also analyzed. All of these clues are combined to reach a final decision.
Short-Circuit Current of Wind Turbines With Doubly Fed Induction Generator
(2007)

The short-circuit current contribution of wind turbines has not received much attention so far. This paper considers the short-circuit behavior, especially the short-circuit current of wind turbines with a doubly fed induction generator. Mostly, these wind turbines have a crowbar to protect the power electronic converter that is connected to the rotor windings of the induction generator. First, the maximum value of the short-circuit current of a conventional induction machine is determined. The differences between a crowbar-protected doubly fed induction generator and a conventional induction generator are highlighted and approximate equations for the maximum short-circuit current of a doubly fed induction generator are determined. The values obtained in this way are compared to the values obtained from time domain simulations. The differences are less then 15%
Game Theory in Wireless Networks: A Tutorial
(2006)

The behavior of a given wireless device may affect the communication capabilities of a neighboring device, notably because the radio communication channel is usually shared in wireless networks. In this tutorial, we carefully explain how situations of this kind can be modelled by making use of game theory. By leveraging on four simple running examples, we introduce the most fundamental concepts of non-cooperative game theory. This approach should help students and scholars to quickly master this fascinating analytical tool without having to read the existing lengthy, economics-oriented books. It should also assist them in modelling problems of their own.
Cryptography and cryptanalysis for embedded systems
(2010)

A growing number of devices of daily use are equipped with computing capabilities. Today, already more than 98 % of all manufactured microprocessors are employed in embedded applications , leaving less than 2 % to traditional computers. Many of these embedded devices are enabled to communicate amongst each other and form networks. A side effect of the rising interconnectedness is a possible vulnerability of these embedded systems. Attacks that have formerly been restricted to PCs can suddenly be launched against cars, tickets, ID cards or even pacemakers. At the same time the security awareness of users and manufacturers of such systems is much lower than in classical PC environments. This renders security one key aspect of embedded systems design and for most pervasive computing applications. As embedded systems are usually deployed in large numbers, costs are a main concern of system developers. Hence embedded security solutions have to be cheap and efficient. Many security services such as digital signatures can only be realized by public key cryptography. Yet, public key schemes are in terms of computation orders of magnitude more expensive than private key cryptosystems. At the same time the prevailing schemes rely on very similar security assumptions. If one scheme gets broken, almost all cryptosystems employing asymmetric cryptography become useless. The first part of this work explores alternatives to the prevailing public key cryptosystems. Two alternative signature schemes and one public key encryption scheme from the family of post quantum cryptosystems are explored. Their security relies on different assumptions so that a break of one of the prevailing schemes does not affect the security of the studied alternatives. The main focus lies on the implementational aspects of these schemes for embedded systems. One actual outcome is that, contrary to common belief, the presented schemes provide similar and in some cases even better performance than the prevailing schemes. The presented solutions include a highly scalable software implementation of the Merkle signature scheme aimed at low-cost microprocessors. For signatures in hardware an FPGA framework for implementing a family of signature schemes based on multivariate quadratic equations is presented. Depending on the chosen scheme, multivariate quadratic signatures show better performance than elliptic curves in terms of area consumption and performance. The McEliece cryptosystem is an alternative public key encryption scheme which was believed to be infeasible on embedded platforms due to its large key size. This work shows that by applying certain …
Recall of childhood trauma: a prospective study of women's memories of child sexual abuse.
(1994)

One hundred twenty-nine women with previously documented histories of sexual victimization in childhood were interviewed and asked detailed questions about their abuse histories to answer the question "Do people actually forget traumatic events such as child sexual abuse, and if so, how common is such forgetting?" A large proportion of the women (38%) did not recall the abuse that had been reported 17 years earlier. Women who were younger at the time of the abuse and those who were molested by someone they knew were more likely to have no recall of the abuse. The implications for research and practice are discussed. Long periods with no memory of abuse should not be regarded as evidence that the abuse did not occur.
Blind Identification of Underdetermined Mixtures by Simultaneous Matrix Diagonalization
(2008)

In this paper, we study simultaneous matrix diagonalization-based techniques for the estimation of the mixing matrix in underdetermined independent component analysis (ICA). This includes a generalization to underdetermined mixtures of the well-known SOBI algorithm. The problem is reformulated in terms of the parallel factor decomposition (PARAFAC) of a higher-order tensor. We present conditions under which the mixing matrix is unique and discuss several algorithms for its computation.
The Internet of Things: A Review of Enabled Technologies and Future Challenges
(2018)

The Internet of Things (IoT) is an emerging classical model, envisioned as a system of billions of small interconnected devices for posing the state-of-the-art findings to real-world glitches. Over the last decade, there has been an increasing research concentration in the IoT as an essential design of the constant convergence between human behaviors and their images on Information Technology. With the development of technologies, the IoT drives the deployment of across-the-board and self-organizing wireless networks. The IoT model is progressing toward the notion of a cyber-physical world, where things can be originated, driven, intermixed, and modernized to facilitate the emergence of any feasible association. This paper provides a summary of the existing IoT research that underlines enabling technologies, such as fog computing, wireless sensor networks, data mining, context awareness, real-time analytics, virtual reality, and cellular communications. Also, we present the lessons learned after acquiring a thorough representation of the subject. Thus, by identifying numerous open research challenges, it is presumed to drag more consideration into this novel paradigm.
THE RESTORATIVE BENEFITS OF NATURE : TOWARD AN INTEGRATIVE
(2004)

Directed attention plays an important role in human information processing; its fatigue, in turn, has far­ reaching consequences. Attention Restoration Theory provides an analysis of the kinds of experiences that lead to recovery from such fatigue. Natural environments turn out to be particularly rich in the character­ istics necessary for restorative experiences. An integrative framework is proposed that places both directed attention and stress in the larger context of human-environment relationships. © 1995 Academic Press Limited